PPT-Operating Systems must support GPU abstractions

Chris Rossbach Microsoft Research Jon Currey Microsoft Research Emmett Witchel University of Texas at Austin HotOS 2011 Lots of GPUs Must they be so hard to use We need dataflow GPU Haiku . All Programmable Abstractions push beyond traditional RTL design methodologies to automate all aspects of system development and algorithm deployment into all programmable FPGAs SoC and 3D ICs Xilinx and its Alliance members are working together to Alan . Gray. EPCC . The University of Edinburgh. Outline. Why do we want/need accelerators such as GPUs?. Architectural reasons for accelerator performance advantages . Latest accelerator Products. NVIDIA and AMD GPUs. Youngho Kim. CIS665: GPU Programming. Building a Million Particle System: Lutz Latta. UberFlow - A GPU-based Particle Engine: Peter Kipfer et al.. Real-Time Particle Systems on the GPU in Dynamic Environments: Shannon Drone. : Operating System Abstractions to Manage GPUs as Compute Devices. Chris Rossbach, Jon Currey, . Microsoft Research. Mark Silberstein, . Technion. Baishakhi Ray, Emmett Witchel, . UT Austin. SOSP October 25, 2011. Watercolor Paint - Abstractions. Watercolor Paint – Non-Representational. Pastel Abstractions. Patrick Cozzi. University of Pennsylvania. CIS 565 - Fall 2014. Acknowledgements. CPU slides – Varun Sampath, NVIDIA. GPU . slides. Kayvon . Fatahalian. , CMU. Mike Houston, . NVIDIA. CPU and GPU Trends. Eurocrypt. May 1. st. , 2017. Rafael Pass, Elaine Shi, . Florian Tramèr. Trusted hardware: . Different . communities. , different . world views. Crypto. Architecture. Systems. & . Security. “Minimal” trusted . . Installation. CS5100 Advanced . Computer Architecture. Introduction. . of. . Gem5-GPU. It. . merges . 2 popular simulators: gem5 and . gpgpu. -sim. Simulates . CPUs, GPUs, and the interactions between . Add GPUs: Accelerate Science Applications. © NVIDIA 2013. Small Changes, Big Speed-up. Application Code. . GPU. C. PU. Use GPU to Parallelize. Compute-Intensive Functions. Rest of Sequential. CPU Code. Dictionary ADT. : Arrays, Lists and . Trees. Kate Deibel. Summer 2012. June 27, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Where We Are. Studying the absolutely essential ADTs of computer science and classic data structures for implementing them. History and Hardware. 1: Operating Systems Overview. 2. This is the simplest animal with a “brain”. Caenorphabditis elegans. C. elegans.  is one of the simplest organisms with a nervous system. This system comprises 302 neurons the pattern of which has been comprehensively mapped, in what is known as a connectome. . Page 121-131. It’s a Windows World. Chapter 6: Alternative Operating Systems. 2. Page 121. What is the OS sitting on our desks?. Windows > 90%. It’s a Windows World. Chapter 6: Alternative Operating Systems. Disjoint Set Union-Find . and . Minimum Spanning Trees. Kate Deibel. Summer 2012. August 13, 2012. CSE 332 Data Abstractions, Summer 2012. 1. Making Connections. You have a set of nodes (numbered 1-9) on a network. . Cynthia Lee. CS106B. Today’s Topics. Quick final exam discussion. Details/logistics, topics, sources for practice problems. Quarter wrap-up. Putting it all together: what have we accomplished together this quarter?.